小波分析及其应用__孙延奎

数字基带传输基带信号，指未经调制的信号。这些信号的特征是其频谱从零频或很低频率开始，占据较宽的频带。 基带信号在传输前，必须经过一些处理或者某些变换（如码型变换、波形和频谱变换）才能送入信道中传输。处理或变换的目的是使信号的特性与信道的传输特性相匹配。 数字基带信号是消息代码的波形表示。表示形式有多种，有单极性、双极性波形，归零和非归零波形，差分波形、多电平波形之分，各自有不同的特点。 研究数字基带信号通过加性高斯白噪声信道的传输，并且假设信道除了叠加高斯噪声外，不会对信号产生其他失真。(matlabSimulation(pulse amplitude modulation) modulation signal in AWGN (additive white Gaussian noise AWGN (Additive White Gaussian Noise)) under the channel bit error rate and bit error rate performance, and compared with the theoretical value.)

图像的5/3小波变换的matlab代码。程序简短，易懂。(Image 5/3 wavelet transform matlab code. Program brief and easy to understand.)

labview小波工具箱以及关于小波变换去噪的源程序。(labview wavelet toolbox and on the wavelet transform denoising of the source.)

说明：  小波标架的共轭梯度算法（Mallat，信号处理的小波导引）(Conjugate gradient algorithm for computing daul function.)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

说明：  小波变换用于脑电信号处理，可以很好的对脑电信号进行时频分析(Wavelet transform for EEG signal processing, can be very good for time-frequency analysis of EEG)

基于小波变换的图像量化编解码，使用零树编码方法(based on wavelet transform quantitative image codecs, the use of zero-tree coding method)

说明：  地震勘探中小波变换，去噪，对初学者容易上手，运用maltlab编写，运行也方便，(Wavelet transform and denoising in seismic exploration)

说明：  很详细的hht编程代码，matlab亲测可用，提供了比较清晰的注释，帮助理解(Very detailed HHT programming code, matlab pro test available, provides a relatively clear note to help understand)

采用小波变换的方法实现心电信号的滤波，分别使用了硬阈值、软阈值和改进阈值方法，并实现了滤波效果的评价（均方差和信噪比）(Wavelet transform of ECG signal filtering method, respectively, using a hard threshold and soft threshold and improve the threshold method, and to achieve the filtering effect of the evaluation (both variance and signal to noise ratio))